Large business organizations utilize a variety of computer and software systems to manage their operations. Such systems are typically designed to focus on a particular sector of the operation, such as finance, inventory control or manufacturing routing. The development of systems to solve particular needs often results in users having to consult a number of distinct systems to gather the information needed to make business decisions. To compound the problem, data is often managed by “legacy” systems or otherwise older computer systems and architectures. These systems typically utilize older technology and are often difficult to integrate with newer enterprise systems.
To effectively manage a business, operations data needs to be up to date and readily available so decisions can be made quickly. A number of solutions have been proposed which translate data between a variety of databases. These solutions often allow for the querying of multiple disparate databases. While these solutions allow the interrogation of multiple databases, they often require complicated queries that have disadvantages of being difficult to use and modify by average business users. Additionally, these systems typically require the user to “drill down” through multiple layers of data if the user requires lower level information. For example, determining the inventory level for a particular manufacturing facility. This often results in an overload of data for the user, further complicating the decision making process.
These solutions also tend to be restricted to a limited portion of the business” computer network and thus not available when the user is away from the office, or does not have access to a networked computer.
Accordingly, it is considered advantageous to have a system that can quickly provide critical business data to a user independent of their location. It is further considered advantageous to provide a system which filters this data to provide the data that is most relevant to the users present location.